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Robotics Controls Engineer

Job in Cambridge, Middlesex County, Massachusetts, 02140, USA
Listing for: Groupe-Ebra-1
Full Time position
Listed on 2026-08-23
Job specializations:
  • Software Development
    Software Testing, Embedded Systems/ Firmware/ IoT
Salary/Wage Range or Industry Benchmark: 120000 - 180000 USD Yearly USD 120000.00 180000.00 YEAR
Job Description & How to Apply Below

Here at Humanoid, we believe in a future where robots amplify human potential. That’s why we’ve set out on a mission to build the world’s most capable, commercially-scalable, and safe humanoid robots. We’re bringing that mission to life with HMND‑01 Alpha - our rapidly developed humanoid platform now running in real industrial pilots - and we’re growing the team to take it even further.

About

the Role

We are looking for a Controls Engineer to join our Control Team in Boston.

You will own how we know our controls stack works: the testing and validation infrastructure that turns "it looked fine on the robot" into measured, reproducible evaluation, the observability and failure analysis that makes runtime behaviour visible and failures shareable, and the documentation and runbooks that let the team self-serve without institutional knowledge. You will also strongly contribute to first-time bring-up of new hardware for Boston components and validate changes end-to-end on real robots before the wider team depends on them.

The ideal candidate has strong control fundamentals
, solid software engineering discipline across the stack - from control code to test harnesses to diagnostic tooling - and the debugging instincts that only come from real hardware. You will work across the whole control stack and be the person the team relies on to tell them the truth about their code.

What You'll Do

Testing & Validation Infrastructure:

  • Build and own hardware-in-the-loop (HIL) and integration test workflows that quantify controller and motion repeatability and accuracy - turning "it looked fine on the robot" into measured, reproducible evaluation.

  • Define and implement repeatability and accuracy metrics for controller and motion changes, and the harnesses that make those measurements consistent across runs and across robots.

  • Expand unit and integration test coverage across the controls components the team actually runs - actuator drivers, hardware interfaces, whole-body control, and the teleoperation pipeline.

  • Develop automated regression checks that surface controls regressions - in accuracy, repeatability, or behaviour - in simulation and on hardware before they reach the wider team.

  • Work with controls engineers to define testability requirements for new components and algorithms, so things are built to be evaluated and validated.

  • Package controllers into cleanly separable, reusable, and easily testable interfaces - so individual controllers can be developed, swapped, and validated in isolation.

New Hardware Bring-Up & Integration:

  • Strongly contribute to first-time bring-up of new hardware for Boston components, and to their integration into the controls stack.

  • Validate hardware and software changes end-to-end on real robots before broader team use - structured, documented, and repeatable.

Debugging, Observability & Failure Analysis:

  • Instrument the controls stack to improve visibility into runtime behaviour - logging, tracing, and diagnostic tooling.

  • Reproduce hardware and software failures in structured, developer-shareable formats; feed structured root-cause context back to algorithm and hardware owners.

  • Identify and resolve cross-stack failure modes that span controls, firmware, and hardware.

Documentation & Knowledge Transfer:

  • Write and maintain engineering documentation for the controls stack: HIL and test coverage, and bring-up/integration guides for new hardware.

  • Own runbooks that let controls engineers self-serve validation, integration, and recovery without relying on institutional knowledge.

What We're Looking For
  • Substantial hands-on robotics experience on real hardware.

  • Strong control theory foundation (joint-space control, PID and feed forward, impedance/admittance, observers, state estimation, filtering, stability) — enough to define meaningful repeatability and accuracy metrics for a control stack and interpret what they say.

  • Shipped software across the stack: modern C++ inside a real-time control codebase, plus Python for test harnesses, analysis and tooling.

  • Built test automation, HIL or integration-test infrastructure for complex physical systems — and got other engineers to actually use it.

  • Solid measurement and data…

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